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We use a unique, hand-collected data set to examine learning and forgetting in hip replacement surgery as a function of a surgeon's experience with specific surgical device versions and the time between their repeat uses. We also develop a generalizable method to correct for the left censoring of device-version-specific experience variables that is a common problem in highly granular experience data, using maximum simulated likelihood estimation with simulation over unobservables conditional on observables. Even for experienced surgeons, the first use of certain device versions can result in at least a 32.4% increase in surgery duration, hurting quality and productivity. Furthermore, with the passage of time, surgeons can forget knowledge gained about the use of particular devices. For certain devices, when the time gap between repeat uses increases from its median to its 75th percentile, surgery duration increases by about 3.4%. The high productivity and quality costs associated with device variety suggest that the gain from a new device design needs to be large enough to compensate for the short-term disadvantages of starting up on a new learning curve and of increasing the chances of knowledge depreciation over time. History: Accepted by Serguei Netessine, operations management. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2016.2721. Keywords: product variety * learning and forgetting * experience curves * productivity * healthcare, 1. Introduction Employees in industries as diverse as information technology (IT) support, auto servicing and repair, healthcare, home loans and mortgages, investment banking, and retail customer service work with a [...]

To authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1468-2354.2009.00566.x Byline: David Byrne ([dagger]), Michelle S. Goeree ([dagger]), Bridget Hiedemann ([dagger]), Steven Stern (1) Abstract: We use the 1993 wave of the Assets and Health Dynamics Among the Oldest Old (AHEAD) data set to estimate a game-theoretic model of families' decisions concerning the provision of informal and formal care for elderly individuals. The outcome is the Nash equilibrium where each family member jointly determines her consumption, transfers for formal care, and allocation of time to informal care, market work, and leisure. We use the estimates to decompose the effects of adult children's opportunity costs, quality of care, and caregiving burden on their propensities to provide informal care. We also simulate the effects of a broad range of policies of current interest. Author Affiliation: ([dagger])Federal Reserve Board, U.S.A.; University of Zurich, Switzerland, University of Southern California, U.S.A.; University of Seattle, U.S.A.; University of Virginia, U.S.A.

To purchase or authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1468-2354.2006.00385.x Byline: Michael J. Brien ([dagger]), Lee A. Lillard ([dagger]), Steven Stern (1) Abstract: The objective of this research is to further our understanding of how and why individuals enter and leave coresidential relationships. We develop and estimate an economic model of nonmarital cohabitation, marriage, and divorce that is consistent with current data on the formation and dissolution of relationships. Jovanovic's (Journal of Political Economy 87 (1979), 972-90) theoretical matching model is extended to help explain household formation and dissolution behavior. Implications of the model reveal what factors influence the decision to start a relationship, what form this relationship will take, and the relative stability of the various types of unions. The structural parameters of the model are estimated using longitudinal data from a sample of female high school seniors from the United States. New numerical methods are developed to reduce computational costs associated with estimation. The empirical results have interesting interpretations given the structural model. They show that a significant cause of cohabitation is the need to learn about potential partners and to hedge against future bad shocks. The estimated parameters are used to conduct several comparative dynamic experiments. For example, we show that policy experiments changing the cost of divorce have little effect on relationship choices. Author Affiliation: ([dagger])Deloitte Financial Advisory Services LLP, Washington, DC, U.S.A.; University of Michigan, U.S.A. (deceased); University of Virginia, U.S.A.

The objective of this research is to further our understanding of how and why individuals enter and leave coresidential relationships. We develop and estimate an economic model of nonmarital cohabitation, marriage, and divorce that is consistent with current data on the formation and dissolution of relationships. Jovanovic's (Journal of Political Economy 87 (1979), 972-90) theoretical matching model is extended to help explain household formation and dissolution behavior. Implications of the model reveal what factors influence the decision to start a relationship, what form this relationship will take, and the relative stability of the various types of unions. The structural parameters of the model are estimated using longitudinal data from a sample of female high school seniors from the United States. New numerical methods are developed to reduce computational costs associated with estimation. The empirical results have interesting interpretations given the structural model. They show that a significant cause of cohabitation is the need to learn about potential partners and to hedge against future bad shocks. The estimated parameters are used to conduct several comparative dynamic experiments. For example, we show that policy experiments changing the cost of divorce have little effect on relationship choices.

We present a structural model of how families decide who should care for elderly parents. We use data from the National Long-Term Care Survey to estimate and test the parameters of the model. Then we use the parameter estimates to simulate the effects of the existing long-term trends in terms of the common but untested explanations for them. Finally, we simulate the effects of alternative family bargaining rules on individual utility to measure the sensitivity of our results to the family decision-making assumptions we make.

Structural estimation process aided by computers has become a common mode of computational economics. Simulated-based estimation provides an efficient and fast ways on coming up with economic forecast across various industries.

This paper modifies and uses the semiparametric methods of Ichimura and Lee (1991) on standard cross-section data to decompose the effect of disability on labor force participation into a demand and a supply effect. It shows that straightforward use of Ichimura and Lee leads to meaningless results while imposing monotonicity on the unknown function leads to substantial results. The paper finds that supply effects dominate the demand effects of disability. Key words: Disability; Labor force participation; Wage equation; Semiparametric estimation; Isotonic regression JEL classification: C14; J22

ABSTRACT This paper estimates the effects of various parent and child characteristics on the choice of care arrangement of the parent taking into account the potential endogeneity of some of [...]

This article considers a model in which the productivity of a worker depends on his experience, ability, and position in the firm. It is shown that workers are sorted in positions based on comparative advantage. Furthermore, workers are induced to retire when productivity is equal to the value of time after adjusting for the reallocation of other workers by positions that would occur if the worker retired.

We estimate a dynamic programming model of job exit behavior and retirement using the method of simulated moments. The model and estimation method allow for both unobserved individual effects and unobserved job-specific 'match' effects. The model is estimated using two different assumptions about individual discount factors. First, a static model, with the discount factor [beta] equal to zero, is estimated. Then a dynamic model, with [beta] = .95, is estimated. In both models, it is found that bad health, age, and lack of education increase the probability of retirement. The dynamic model performs better than the static model and has different implications for retirement behavior. The job-specific effects are an important source of unobserved heterogeneity.

The education for the healthcare profession among different races is investigated using evidence from the NLS-72. Findings highlight the role of pre-collegiate factors in the choice to pursue a medical education. A model of postsecondary decisions that include degree completion, college type, enrollment is also presented.

Data from the National Long Term Care Survey is used to model the caregiving decisions of adult children of elderly parents, focusing on the shared responsibilities of siblings. Topics include how family characteristics impact care decisions.

This paper estimates the effect of disability on labor force participation by using symptoms of diseases as instruments in a simultaneous equations model of endogenous reported disability and labor force participation. The results show that each measure of disability explains a significant amount of variation in labor force participation, thought the two are not perfect substitutes. There is only weak evidence of endogeneity of the disability variables. For cases where there is evidence of endogeneity, the bias it causes has the opposite effect of that hypothesized in the literature (i.e., stress causes health to deteriorate with labor force participation). Furthermore, it has only insignificant effects on the coefficients for other variables. (Reprinted by permission of the publisher.)

A strategic model was presented which illustrate the type of care given by a family to an elderly parent. The model, which utilizes data from the National Long-term Care Survey, shows that mothers are more likely to be taken care of by their children than fathers. It also reveals that compared to daughters, sons are less likely to take care of their parents. The distance between parent and the child exerts a negative effect on family members' valuation of care that is provided by a child.

This paper develops a semiparametric estimation approach for mixed count regression models based on series expansion for the unknown density of the unobserved heterogeneity. We use the generalized Laguerre series expansion around a gamma baseline density to model unobserved heterogeneity in a Poisson mixture model. We establish the consistency of the estimator and present a computational strategy to implement the proposed estimation techniques in the standard count model as well as in truncated, censored, and zero-inflated count regression models. Monte Carlo evidence shows that the finite sample behavior of the estimator is quite good. The paper applies the method to a model of individual shopping behavior. Keywords: Poisson regressions; Unobserved heterogeneity; Series approximation; Overdispersion; Censoring; Zero inflation